Literature search
library(tidyverse)
library(DT)
#Search terms####
search.terms <- read_csv("data/search.terms.csv")
datatable(search.terms)
total.lit <- search.terms %>% filter(search != "final")
total.lit
## # A tibble: 6 × 3
## search terms hits
## <chr> <chr> <int>
## 1 1 plant facilitat* niche* arid* 47
## 2 2 plant facilitat* niche* desert* 32
## 3 3 nurse plant* niche* arid 16
## 4 4 nurse plant* niche* desert 11
## 5 5 positive interact* niche* desert* 21
## 6 6 positive interact* niche* arid* 29
totals <- sum(total.lit$hits)
totals
## [1] 156
final.list <- 53
totals-final.list
## [1] 103
#PRISMA####
#use 'prisma' function from PRISMAstatement
#https://cran.r-project.org/web/packages/PRISMAstatement/vignettes/PRISMA.html
prisma.report <-read_csv("data/prisma.csv")
prisma.report
## # A tibble: 53 × 4
## ID inclusion category
## <int> <chr> <chr>
## 1 1 N no positive interactions recorded
## 2 2 Y include
## 3 3 Y include
## 4 4 N no niche expansion recorded
## 5 5 Y include
## 6 6 N no positive interactions recorded
## 7 7 N no positive interactions recorded
## 8 8 N no positive interactions recorded
## 9 9 Y include
## 10 10 Y include
## # ... with 43 more rows, and 1 more variables: detailed.reason <chr>
exclusions <- prisma.report %>% filter(inclusion == "N") %>% select(ID, category)
dim(exclusions)
## [1] 24 2
library(PRISMAstatement)
prisma(found = 156,
found_other = 0,
no_dupes = 53,
screened = 53,
screen_exclusions = 0,
full_text = 53,
full_text_exclusions = 24,
qualitative = 0,
quantitative = 29,
width = 800, height = 800)
#Summary of exclusions
categories <- exclusions %>% group_by(category) %>% tally() %>% arrange(desc(n))
categories
## # A tibble: 6 × 2
## category n
## <chr> <int>
## 1 no nurse plant 9
## 2 no positive interactions recorded 9
## 3 no niche expansion recorded 2
## 4 review 2
## 5 language 1
## 6 not desert 1
ggplot(categories, aes(category, n)) + geom_bar(stat = "identity") + coord_flip() + ylim(0,10)
